One challenging issue of OLED technology is the degradation characterized by the loss of luminance over time due to cumulative usage or current driven through its emitting pixels. Because an OLED display typically comprise of thousands to millions self-emitting color pixels, the degradation rate among pixels are different due to un-even usage. Further, the degradation rate is different for each of the three primary colors of a pixel. For example, a blue sub-pixel degrades faster than red and green sub-pixels. Differences in degradation rate for pixels accumulates over time to cause undesirable effects such as color shift or burn-in, sometime also called image sticking. This is one of the key challenges that needs to be solved to enable wide adoption of OLED displays in many applications, such as personal computing, where many applications user interface graphics are susceptible to image sticking. To overcome this issue, compensation techniques can be applied to OLED to minimize or eliminate the burn-in or image sticking effect.
To compensate for the gradual loss of luminance that OLED displays experience over time, a common technique is to track the display sub-pixel operating history to figure out how much its luminance has degraded. Based on this pixel-history data, certain algorithms could be applied to generate correcting values to compensate for the degradation. Such values could then be input into another algorithm that determines the transformation that needs to be performed on each incoming sub-pixel in the frame buffer to counteract image stickiness. Such an image-transformation algorithm also consumes significant power and (depending on how it is implemented) could negatively impact overall system performance. Applying the algorithms at sub-pixel level consumes most memory, needs most power, but generates best quality. When these algorithms are applied at a larger granularity (e.g., a block of pixels), the solution consumes less power and reduces the per-frame processing time, but it reduces the quality of the image and negatively impacts long term effectiveness of the product. Such challenges could limit use of these techniques in product designs.
The same numbers are used throughout the disclosure and the figures to reference like components and features. Numbers in the 100 series refer to features originally found in FIG. 1; numbers in the 200 series refer to features originally found in FIG. 2; and so on.